Why can’t professional macroeconomic forecasters predict recessions?

The professional forecasters’ inability to anticipate macroeconomic recessions is well documented. The literature has found that aggregate or consensus forecasts are too optimistic before downturns and too pessimistic before recoveries. This paper explores whether this result also holds with individual data. Using a Spanish survey of professional forecasters conducted by Funcas, I find that forecasters are indeed too optimistic before recessions for two reasons. First, strong herding behaviour around the consensus forecast prevents those forecasters perceiving the early signs of a recession from adjusting their expectations as much as needed to predict it. And second, some forecasters put too much weight on the most recent developments when producing their forecasts and fail to fully account for the reversion to the mean embedded in the data-generating process. Both factors lead to negative forecast errors when a recession occurs. Consequently, professional forecasters could improve their forecasting performance by placing less weight on indicators from the recent past and by avoiding inefficient herding

Do Professional Forecasters Behave as if They Believed in the New Keynesian Phillips Curve for the Euro Area?

This paper finds that participants in the European Central Bank’s Survey of Professional Forecasters have submitted forecasts that are consistent with a (mostly forward-looking) New Keynesian Phillips Curve for the euro area. The estimation results suggest that euro-area inflation forecasts have reacted less to unemployment forecasts after the start of the financial crisis but another cost measure (energy inflation) remains significant. This finding is consistent with the claim by the International Monetary Fund that the Phillips Curve has recently become flatter in the euro area. However, the reasons suggested by the Fund for this finding, namely a better anchoring of inflation expectations and increases in structural unemployment do not seem to find support in the survey data. Instead, downward wage rigidities may be playing a prominent role

Measures of macroeconomic uncertainty for the ECB’s survey of professional forecasters

This paper investigates to what extent different uncertainty measures commonly used in the SPF literature comply with a few reasonable properties. The measures published by the ECB in its quarterly report of the SPF results do not verify almost any of the properties. Unfortunately, the alternatives typically proposed in the literature do not perform much better under this metric. Instead, entropy-based measures and a new measure based on the Gini index seem more satisfactory in this regard. Independently of the measure chosen, the aggregation of the results from all the participants in each survey round may produce misleading results: they may compound true changes in uncertainty with artificial changes due to the variations in the panel of respondents to the survey. Using an aggregate measure of uncertainty from the subsets of forecasters that replied to two consecutive survey rounds, the paper finds significant increases in macroeconomic uncertainty in the euro area from 2001 to 2004, declines in uncertainty from the second half of 2004 to 2007, sharp increases from 2008 to mid-2009 and falls thereafter with the exception of the relatively more turbulent period between late 2011 and early 2012

Weighted Averages of Individual Measures of Uncertainty from the European Central Bank’s Survey of Professional Forecasters

This paper explores to what extent aggregate measures of uncertainty calculated with data from the European Central Bank’s Survey of Professional Forecasters change when higher weights are given to the data submitted by more accurate forecasters. It is found that these weighted measures suggest higher levels of uncertainty than those obtained with unweighted methods. This result comes from the finding that forecasters with better scores are characterised by higher levels of individual uncertainty, a feature that is robust to the use of different scoring rules and different measures of uncertainty. It is thereby suggested that the European Central Bank could use weighted measures of aggregate uncertainty to complement the assessment obtained from standard unweighted methods

Informe mensual del mercado de trabajo de la comarca de Cartagena: marzo de 2020

El número total de parados en la Comarca de Cartagena en marzo de 2020 se situó en 30.310 personas (ver tabla 1), lo que supone un incremento de 1.858 parados respecto al mes de febrero (ver tabla 2), un 6,5% más (ver tabla 3). Este dato evidencia que la Comarca empieza a sentir los efectos económicos asociados a la crisis sanitaria provocada por el coronavirus. El desempleo subió en marzo en todos los sectores productivos, con especial impacto sobre la construcción (+19,7%) y la industria (+12,9%)

Informe mensual del mercado de trabajo de la comarca de Cartagena: abril de 2020

El número total de parados en la Comarca de Cartagena en abril de 2020 se situó en 32.377 personas (ver tabla 1), lo que supone un incremento de 2.067 parados respecto al mes de marzo (ver tabla 2), un 6,8% más (ver tabla 3). Este dato evidencia que los efectos económicos negativos asociados a la crisis sanitaria provocada por el coronavirus se acentuaron en abril. El desempleo subió en todos los sectores productivos, con especial impacto sobre la construcción y la industria (ambos +8,4%)