Purpose

This 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/approach

This 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.

Findings

The 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 implications

Evaluating 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/value

The 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.

中文翻译：

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评估基于调查的利率和宏观经济变量预测

目的

本研究使用替代方法研究设计检查参与蓝筹经济指标调查的专业分析师的预测表现。

设计/方法/方法

这项工作采用两种方法，即面板规范，横截面是预测范围（从 1 个月到 18 个月的提前预测），时间段是进行预测的时间和分位数回归技术，它评估预测和被预测的目标变量之间隐藏的非单调关系。

发现

本研究的实证结果表明，基于调查的某些关键宏观经济变量的预测普遍存在偏差，但仍然是目标变量的有效预测因子。特别是，我们发现调查参与者在预测长期利率和短期利率方面的效率更高，而中期利率的可预测性最不准确。最后，我们的实证分析表明，货币波动在短期内很难预测，而我们表明基于调查的预测是 GDP 平减指数和增长最准确的预测指标之一。

实际影响

评估经济预测的准确性至关重要，因为市场参与者和政策制定者利用此类数据（作为多种输入之一）进行投资、金融和政策决策。因此，决策的质量部分取决于预测的质量。我们的实证结果应该对使用利率和通胀预测作为变量的资产定价模型产生直接影响。

原创性/价值

本研究标志着与现有实证尝试的方法论背离，因为它提出了一种更简单但功能强大的方法来调查专业预测的效率。所采用的经验规范使市场参与者能够调查不同预测范围内预测的信息内容和预测质量的时间演变。