A textual analysis of Bank of England growth forecasts

Jones, Jacob T.; Sinclair, Tara M.; Stekler, H. O.

doi:10.1016/j.ijforecast.2019.05.015

Cited by 10 publications

(9 citation statements)

References 13 publications

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“…German forecasters' narratives can enhance the accuracy of German business cycle forecasts. Overall, the results are in line with the findings of Jones et al (2020), Sharpe et al (2020) and Clements and Reade (2020). The four-quarter forecast horizon is comparable with the results of Sharpe et al (2020) for the Fed's Greenbook, whereas findings for the UK show shorter forecast horizons (Jones et al 2020;Clements and Reade 2020).…”

Section: Discussionsupporting

confidence: 87%

“…One strand will be subsumed here under the term 'elicited forecasts', which was used by Jones et al (2020). This concept applies a manual scoring procedure to quantify qualitative assessments about the future stance of the economy.…”

Section: Introductionmentioning

confidence: 99%

“…Lundquist and Stekler 2012;Stekler and Symington 2016;Mathy and Stekler 2018). The recent analysis of Jones et al (2020) investigates the Bank of England's growth forecasts using elicited forecasts over the period 2005-2015. The more general research question as to whether the text contains additional information for the numerical forecasts is similar to this work. Jones et al (2020) find that the economic development in the UK is accurately represented by the elicited forecasts.…”

Section: Introductionmentioning

confidence: 99%

“…The recent analysis of Jones et al (2020) investigates the Bank of England's growth forecasts using elicited forecasts over the period 2005-2015. The more general research question as to whether the text contains additional information for the numerical forecasts is similar to this work. Jones et al (2020) find that the economic development in the UK is accurately represented by the elicited forecasts. Moreover, regression results suggest informational content of the text index in the sense that they can improve the Bank of England's numerical growth nowcasts and one-quarter-ahead forecasts.…”

Section: Introductionmentioning

confidence: 99%

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German forecasters’ narratives: How informative are German business cycle forecast reports?

Müller

2021

Empir Econ

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Based on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters’ narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

German forecasters’ narratives: How informative are German business cycle forecast reports?

Müller

2021

Empir Econ

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“…In that sense, our study is related to Asquith, Mikhail and Au (2005), which examines how the sentiment of the text in Wall Street analyst reports explains firms' stock price responses to earnings forecast revisions. Even more similar, Jones, Sinclair and Stekler (2019) quantifies the narrative contained in Bank of England inflation reports and finds that text to contain information that helps predict quarter-ahead inflation.…”

Section: Introductionmentioning

confidence: 99%

The Power of Narratives in Economic Forecasts

Sharpe

Sinha

Hollrah

2020

FEDS

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We apply textual analysis tools to the narratives that accompany Federal Reserve Board economic forecasts to measure the degree of optimism versus pessimism expressed in those narratives. Text sentiment is strongly correlated with the accompanying economic point forecasts, positively for GDP forecasts and negatively for unemployment and inflation forecasts. Moreover, our sentiment measure predicts errors in FRB and private forecasts for GDP growth and unemployment up to four quarters out. Furthermore, stronger sentiment predicts tighter than expected monetary policy and higher future stock returns. Quantile regressions indicate that most of sentiment's forecasting power arises from signaling downside risks to the economy and stock prices.

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