Survey-based Forecasts Research Articles

The Anchoring of US Inflation Expectations Since 2012

The stabilization, or anchoring, of inflation expectations at a target can help a central bank meet its goals. This paper develops a measure of expectations’ anchoring that combines the deviation of a consensus forecast from an inflation target with forecaster disagreement. We apply the measure to survey-based forecasts of PCE price inflation at medium- and longer-run horizons. Following the FOMC’s 2012 announcement of a 2 percent inflation target, the anchoring of both forecast series steadily improved through 2020:Q4. Recently, while longer-run expectations have remained well-anchored, the anchoring of medium-run expectations weakened significantly during the pandemic before strengthening in 2023:Q1.

Uniform Nonparametric Inference for Spatially Dependent Panel Data

This article proposes a uniform functional inference method for nonparametric regressions in a panel-data setting that features general unknown forms of spatio-temporal dependence. The method requires a long time span, but does not impose any restriction on the size of the cross section or the strength of spatial correlation. The uniform inference is justified via a new growing-dimensional Gaussian coupling theory for spatio-temporally dependent panels. We apply the method in two empirical settings. One concerns the nonparametric relationship between asset price volatility and trading volume as depicted by the mixture of distribution hypothesis. The other pertains to testing the rationality of survey-based forecasts, in which we document nonparametric evidence for information rigidity among professional forecasters, offering new support for sticky-information and noisy-information models in macroeconomics.

Are consensus FX forecasts valuable for investors?

We establish a new link between the cross-section of currency returns and survey-based forecasts. Using data from Consensus Economics, we show that surveys provide trading signals which are not entirely driven by standard benchmark trading strategies such as momentum, carry, or value. We evidence the sizable economic value of survey-based trading strategies, as they provide additional excess returns of up to two percentage points per year compared to benchmarks. This illustrates that professionals effectively explore available information and that their expertise can be used to diversify exchange rate portfolios. Our findings are robust against various tests and different currency portfolios structures.

Evaluating survey-based forecasts of interest rates and macroeconomic variables

PurposeThis study examines the forecasting performance of the professional analysts participating in the Blue Chip Economic Indicators Survey using an alternative methodological research design.Design/methodology/approachThis work employs two methodologies, namely a panel specification, with the cross-section being the forecast horizon (from 1-month to 18-months ahead forecasts) and the time period being the time that the forecast was made and a quantile regression technique, which evaluates the hidden nonmonotonic relations between the forecasts and the target variables being forecasted.FindingsThe empirical findings of this study show that survey-based forecasts of certain key macroeconomic variables are generally biased but still efficient predictors of target variables. In particular, we find that survey participants are more efficient in predicting long-term interest rates in the long-run and short-term interest rates in the short run, while the predictability of medium-term interest rates is the least accurate. Finally, our empirical analysis suggests that currency fluctuations are very hard to predict in the short run, while we show that survey-based forecasts are among the most accurate predictors of GDP deflator and growth.Practical implicationsEvaluating the accuracy of economic forecasts is critical since market participants and policymakers utilize such data (as one of several inputs) for making investment, financial and policy decisions. Therefore, the quality of a decision depends, in part, on the quality of the forecast. Our empirical results should have immediate implications for asset pricing models that use interest rates and inflation forecasts as variables.Originality/valueThe present study marks a methodological departure from existing empirical attempts as it proposes a simpler yet powerful approach in order to investigate the efficiency of professional forecasts. The employed empirical specifications enable market participants to investigate the information content of forecasts over different forecast horizons and the temporal evolution of forecast quality.

Oil prices and experts’ forecasts of seven exchange rates

ABSTRACT Research indicates that survey-based forecasts of exchange rates fail to be rational. In addition, the literature points to oil prices as a key factor in determining/predicting exchange rates. We investigate these two research topics by focusing on Blue Chip multi-month forecasts of seven exchange rates for 1999–2015. Our investigation utilizes the recent forecast evaluation method that allows for the possibility of asymmetric loss. We show that Blue Chip forecasts, while free of systematic bias, cannot beat the random walk benchmark, and, at some forecast horizons, the errors fail to be orthogonal to changes in oil prices. We further show that, for four out of seven exchange rates, the change in oil prices explains the information content difference between the Blue Chip and random walk forecasts. Put together, our findings suggest that the inaccuracy of Blue Chip forecasts may be in part due to an inefficient use of oil price information available at the time of the forecast and, thus, forecasters should pay special attention to oil price movements when forecasting exchange rates.

Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile

We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the driftless random walk in terms of mean squared prediction error at several forecasting horizons. A similar result is found when precision is measured in a direction-of-change dimension: survey-based forecasts outperform a “pure luck” benchmark at several forecasting horizons. Our findings suggest that survey-based forecasts of the Chilean exchange rate should be considered as a tough benchmark to beat for economic models, tougher indeed than the traditional driftless random walk.

Forecasting inflation with online prices

Are survey-based forecasts unbeatable? They are not. This paper uses online price indices to forecast the Consumer Price Index. We find that online price indices anticipate changes in official inflation trends more than one month in advance. Our baseline one-month forecast outperforms Bloomberg surveys of forecasters, which only predict the contemporaneous inflation rate. Our baseline specification also outperforms statistical benchmark forecasts for Australia, Canada, France, Germany, Greece, Ireland, Italy, the Netherlands, the United Kingdom, and the United States. Similarly, our quarterly forecast for the US inflation rate substantially outperforms the Survey of Professional Forecasters.

Can We Beat the Random Walk? The Case of Survey-Based Exchange Rate Forecasts in Chile

We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. This result holds true even when comparing the survey to a more competitive benchmark based on a refined information set. A similar result is found when precision is measured in terms of Directional Accuracy: survey-based forecasts outperform a “pure luck” benchmark at several forecasting horizons. Differing from the traditional “no predictability” result reported in the literature for many exchange rates, our findings suggest that the Chilean peso is indeed predictable.

Comparing empirical and survey-based yield forecasts in a dryland agro-ecosystem

Accurate crop yield forecasts before harvest are crucial for providing early warning of agricultural losses, so that policy-makers can take steps to minimize hunger risk. Within-season surveys of farmers’ end-of-season harvest expectations are one important method governments use to develop yield forecasts. Survey-based methods have two potential limitations whose effects are poorly understood. First, survey-based forecasts may be subject to errors and biases in the response data. For example, the weather variables that most impact yields may not be the same as those that farmers consider when shaping their yield expectations, thereby undermining forecast accuracy. Secondly, surveys are typically conducted late in the growing season, giving the government less advance notices of potential crop failures or low yields, and are costly to implement. Here we investigate these limitations within the context of Zambia’s annual Crop Forecast Survey (CFS). Concerning the first limitation, we analyzed the differences between CFS-predicted yields and reported yields collected by Post Harvest Surveys, and found that excess rainfall during the planting stage was more important to the actual yield than to farmers’ yield forecasts. For the second limitation, we evaluated whether a simple empirical yield forecast model could produce earlier and more accurate yield forecasts than the CFS. A random forest model using weather variables, soil texture, and soil pH as predictors were able to produce yield forecasts at the same or higher accuracy since the planting season.

Rationality and forecasting accuracy of exchange rate expectations: Evidence from survey-based forecasts

We examine rationality, forecasting accuracy, and economic value of the survey-based exchange rate forecasts for 10 developed and 23 developing countries at the 3-, 12-, and 24-month horizons. Using the data from two surveys for the period from 2004 to 2012, we find strong evidence that the forecasts for developing countries are biased at all forecast horizons. For developed countries, forecasts are strongly biased at the 3-month horizon, the bias decreases at the 12-month horizon, and increases again at the 24-month horizon. Based on the magnitude of the forecast errors and the direction of change, long-term forecasts are more accurate than short-term forecasts. Economic evaluation of the forecasts indicates that the forecasters are successful at generating positive economic profits, and economic gains of the forecasts for developed countries improve with the forecast horizon.

Rationality and Forecasting Accuracy of Exchange Rate Expectations: Evidence from Survey-Based Forecasts

Rationality and Forecasting Accuracy of Exchange Rate Expectations: Evidence from Survey-Based Forecasts

Predictive accuracy of survey-based forecasts for numbers of filings at the European Patent Office

This study examines the predictive accuracy of the forecasts for patent filings from a sequence of annual surveys of patent applicants at the European Patent Office, particularly regarding the extent to which applicants could foresee the effects of the 2008/2009 recession. It also investigates the possibilities for new methods to calculate forecasts for survey results.Applicants were selected randomly each year, and opinions were sought about numbers of filings in the previous year, the current year and the following two years. It is found that two and three year predictions were better for worldwide first filings than for EPO Total filings (sum of European direct and PCT International Phase filings, excluding divisional filings), and differences are established between main blocs of residence of the applicants in this regard. An investigation is made to examine the possible benefits of indirect transfer forecasts for total EPO filings via worldwide first filings, and of indirect forecasts of PCT regional phase entries from PCT international phase filings. Although the recession was not well anticipated by the applicants, it was slightly better anticipated in terms of worldwide first filings and PCT regional phase entries, than for total EPO filings. A combination approach may be appropriate for future surveys.Suggestions are made for the further development of analysis methods that can be tried out on future surveys.

The term structure of inflation expectations

We use information in the term structure of survey-based forecasts of inflation to estimate a factor hidden in the nominal yield curve. We construct a model that accommodates forecasts over multiple horizons from multiple surveys and Treasury real and nominal yields by allowing for differences between risk-neutral, subjective, and objective probability measures. We establish that model-based inflation expectations are driven by inflation, output, and one latent factor. We find that this factor affects inflation expectations at all horizons but has almost no effect on the nominal yields; that is, the latent factor is hidden. We show that this hidden factor is not related to either current and past inflation or the standard set of macro variables studied in the literature. Consistent with the theoretical property of a hidden factor, our model outperforms a standard macro-finance model in its forecasting of inflation and yields.

Time-variation in term premia: International survey-based evidence

Using a large, previously unexplored data set of survey-based interest rate forecasts that covers a broad range of countries, this paper re-examines the expectations hypothesis of the term structure of interest rates. We find that survey-based interest rate forecasts outperform not only a random walk forecast, but also outperform forecasts from forward rates. When using these superior survey-based forecasts in a modified expectations hypothesis test, the expectations hypothesis is rejected for fewer countries, at lower significance levels, and has greater explanatory power than when using a traditional forward rates-based test. We furthermore document strong time-variation in the term premia, which is an important reason why the traditional expectations hypothesis test is rejected so frequently. This time-variation seems to arise from the changing attitudes towards risk among market participants and as a compensation for the change in liquidity in the term structure. Finally, we find that generalizing findings from earlier U.S. studies to other countries may lead to bias in the true economic relationships in these countries.

How informative are interest rate survey-based forecasts?

This paper studies the information content of survey-based predictions for the Brazilian short-term interest rate. We perform vector autoregression analysis to test for the dynamic relationship between market expectations of interest rates and spot interest rates, and a single regression forecasting approach. Empirical results suggest that surveys may be useful in assessing market expectations (contain relevant information) and in building Central Bank credibility. Within an inflation targeting framework they are crucial in order to receive timely feedback on market sentiment regarding the conduct of monetary policy.

Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty and Risk

In September 2002, a new market in Economic Derivatives was launched allowing traders to take positions on future values of several macroeconomic data releases. We provide an initial analysis of the prices of these options. We find that market-based measures of expectations are similar to survey-based forecasts, although the market-based measures somewhat more accurately predict financial market responses to surprises in data. These markets also provide implied probabilities of the full range of specific outcomes, allowing us to measure uncertainty, assess its driving forces, and compare this measure of uncertainty with the dispersion of point-estimates among individual forecasters (a measure of disagreement). We also assess the accuracy of market-generated probability density forecasts. A consistent theme is that few of the behavioral anomalies present in surveys of professional forecasts survive in equilibrium, and that these markets are remarkably well calibrated. Finally we assess the role of risk, finding little evidence that risk-aversion drives a wedge between market prices and probabilities in this market.

Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk

In September 2002, a new market in "Economic Derivatives" was launched allowing traders to take positions on future values of several macroeconomic data releases. We provide an initial analysis of the prices of these options. We find that market-based measures of expectations are similar to survey-based forecasts, although the market-based measures somewhat more accurately predict financial market responses to surprises in data. These markets also provide implied probabilities of the full range of specific outcomes, allowing us to measure uncertainty, assess its driving forces, and compare this measure of uncertainty with the dispersion of point-estimates among individual forecasters (a measure of disagreement). We also assess the accuracy of market-generated probability density forecasts. A consistent theme is that few of the behavioral anomalies present in surveys of professional forecasts survive in equilibrium, and that these markets are remarkably well calibrated. Finally we assess the role of risk, finding little evidence that risk-aversion drives a wedge between market prices and probabilities in this market.