HICP inflation expectations unchanged for 2018, 2019 and 2020; longer-term expectations stable at 1.9%
Real GDP growth expectations revised down for 2018 and 2019, but unchanged for 2020
Unemployment rate expectations revised down for 2018, 2019 and 2020
The survey began in January 1999 and as such is the longest-running survey of euro area macroeconomic expectations. It is conducted four times a year, in January, April, July and October.
Respondents to the Survey of Professional Forecasters are experts employed by financial or non-financial institutions, such as economic research institutions.
The survey asks for point forecasts and probability distributions for the rates of annual HICP inflation, annual core HICP inflation, real GDP growth and unemployment expected in the euro area at several horizons:
Point expectations for annual growth in compensation per employee, the oil price (in US dollars), the USD/EUR exchange rate and the rate on the ECB’s main refinancing operations at different horizons are also collected.
The results of an additional special survey conducted in 2009 provide information on how frequently respondents typically update their forecasts, the forecasting techniques and models they employ and, specifically, how they generate their probability distributions. A second special survey conducted in 2014 explored how this might have changed following the financial crisis.
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The SPF, for which the full, anonymised microdata are published each quarter, provides a rich source of information for both research and conjunctural analysis, a selection of which is presented here.
Using the SPF microdata, this paper examines the stability of the distribution of long-term inflation expectations in the euro area following the Great Recession. Although mean expectations declined somewhat, they remained quite well anchored to the ECB’s price stability objective and their degree of co-movement with other variables did not increase noticeably. In contrast, long-term inflation uncertainty increased and there was a clear shift toward a more negatively skewed distribution. Such findings are in line with the predictions of theoretical models emphasising the impact of the lower bound on policy rates and uncertainty about monetary transmission. For example, controlling for other factors, announcement dates for non-standard monetary policy measures are shown to be associated with an increase in long-term inflation uncertainty.
This paper analyses the predictive power of market-based and survey-based inflation expectations for actual inflation. Data on inflation swaps and SPF forecasts show that both market-based and survey-based measures have a non-negligible predictive power for inflation developments, as compared to statistical benchmark models. Therefore, for horizons of one and two years ahead, market-based and survey-based inflation expectations actually convey information on future inflation developments.
This paper examines the link between the characteristics of SPF macroeconomic density forecasts (such as their location, spread, skewness and tail risk) and density forecast performance. Controlling for the effects of common macroeconomic shocks, cross-sectional and fixed-effect panel regressions are applied to link density characteristics and density forecast performance. The empirical results suggest that many macroeconomic experts could systematically improve their density performance by correcting a downward bias in their variances. Aside from this shortcoming in second-moment characteristics of the individual densities, other higher-moment features, such as skewness or variation in the degree of probability mass given to the tails of the predictive distributions, tend ¬– as a rule – not to contribute significantly to enhancing individual density forecast performance.
This paper proposes methods to evaluate the risk assessments collected as part of the ECB Survey of Professional Forecasters (SPF). The approach focuses on direction-of-change predictions as well as the prediction of relatively more extreme macroeconomic outcomes located in the upper and lower regions of the predictive densities. For inflation and GDP growth, it finds that surveyed densities are informative about the future direction of change. Regarding more extreme high and low outcome events, the surveys are really only informative about GDP growth outcomes and at short horizons. The upper and lower regions of the predictive densities for inflation are much less informative.
This paper proposes a framework to evaluate the subjective density forecasts of macroeconomists in the SPF. A key aspect is the evaluation of the entire predictive density including an evaluation of the impact of location, spread, skew and tail risk on density forecast performance. Overall, it finds considerable heterogeneity in the performance of the surveyed densities at the individual level. Relative to a set of simple benchmarks, this performance is somewhat better for GDP growth than for inflation, although in the former case it diminishes substantially with the forecast horizon. There was some improvement in the relative performance of expert densities during the recent period of macroeconomic volatility, but also evidence of overconfidence or neglected risks in expert probability assessments, as reflected in frequent occurrences of events which are assigned a zero probability. Moreover, higher-moment features such as skew or the degree of probability mass in their tails are shown not to contribute significantly to improvements in individual density forecast performance.
This paper explores the potential gains from alternative combinations of SPF forecasts, including statistical combinations based on principal components analysis and trimmed means, performance-based weighting, least squares estimates of optimal weights as well as Bayesian shrinkage. A pseudo real-time out-of-sample performance evaluation of these alternative combinations is provided, and a check of the sensitivity of the results to possible data snooping bias using a novel real-time meta selection procedure not subject to the data snooping critique. For GDP growth and the unemployment rate, only a few of the forecast combination schemes are able to outperform the simple equal-weighted average forecast. Conversely, for the inflation rate there is stronger evidence that more refined combinations can lead to improvement on this benchmark. In particular, for this variable, the relative improvement appears significant even controlling for data snooping bias.
This occasional paper provides an initial assessment of the information content of the results from the first eight years of the Survey of Professional Forecasters. It finds that over this period inflation tended to be higher than had been expected, but there was less evidence of any systematic errors for GDP and unemployment forecasts. In addition, assessments of forecast uncertainty based on probability distributions did not seem to capture fully the overall level of macroeconomic uncertainty and, finally, longer-term inflation expectations had been well anchored at rates consistent with the ECB achieving its price stability objective.