The Unassuming Economist

From a paper by Bertrand Candelon and Francesco Roccazzella

“This paper evaluates the informative value of the ECB inflation forecasts vis-à-vis other institutional and model-based forecasts in the euro area using ex post optimal combinations of forecasts and nonnegative weights. From a methodological perspective, we adapt the corresponding forecast encompassing test to the constrained parameter space, showcasing its superior performance over traditional encompassing tests in both size and power properties. Empirically, the combining weights and the forecast encompassing test reveal that the ECB was the most informative forecaster of euro area inflation over the 2009–2021 period. This changed in 2022: The ECB lost its position as the most informative forecaster, and when using rolling windows to estimate the combining weights using a rolling window, we find an important decline in the ECB’s weight over time. This time dependency can be associated with the economic environment and, in particular, the level of uncertainty, the monetary policy, and the macro-financial conditions in which the ECB operates.”

From a paper by Oguzhan Cepni, Abdullah Kazdal, Muhammed Enes Olgun, and Muhammed Hasan Yilmaz:

“This paper investigates whether inflation forecasting in emerging economies can be improved with the inclusion of a global inflation component. Focusing on the headline inflation rate of Türkiye, we implement a forecasting exercise using a large dataset describing domestic macroeconomic as well as global inflation dynamics. Our factor-augmented predictive regression results show that incorporating global inflation factors derived from other emerging markets’ inflation rates enhances forecasting accuracy of the local headline inflation rate. The results are robust to using alternative dimension-reduction methods, including the elastic net technique. Our findings contribute to the current methodological toolkit available to policymakers for predicting inflation in an emerging market context.”

From a paper by James Mitchell, Taylor Shiroff, and Hana Braitsch:

“This paper shows how both the characteristics and the accuracy of the point and density forecasts from a well-known panel data survey of households’ inflationary expectations – the New York Fed’s Survey of Consumer Expectations – depend on the tenure of survey respondents. Households’ point and density forecasts of inflation become significantly more accurate with repeated practice of completing the survey. These learning gains are best identified when tenure-based combination forecasts are constructed. Tenured households on average produce lower point forecasts of inflation, perceive less forecast uncertainty, round their uncertainty but not their point forecasts, report unimodal densities, and provide internally consistent point and density forecasts.”

See the link here.

From a paper by Luciano Vereda, Helder Ferreira de Mendonça, and George Morcerf:

“Our study advances the modelling of forecast revisions by accounting for the nuanced impact of informational shocks across different time horizons. Specifically, we introduce modifications to the error structure of regression models used to detect biases in macroeconomic forecasts. Drawing on consensus forecasts of inflation and output growth from the central banks of Brazil, Chile, and Mexico, our approach offers a nuanced understanding of bias estimation uncertainty, leading to a more robust rejection of the null hypothesis of no biases. By elucidating the differential effects of informational shocks on forecast accuracy across time periods, our findings not only contribute to the refinement of forecasting methodologies but also have implications for policymakers and economic analysts striving for more accurate and reliable predictions in dynamic economic environments.”