Monetary Policy in the Media Spotlight: Sentiments, Signals, and Economic Impact
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866916013371555840 |
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| author | Ayivodji, Firmin Briand, Etienne Moran, Kevin Stevanovic, Dalibor |
| author_facet | Ayivodji, Firmin Briand, Etienne Moran, Kevin Stevanovic, Dalibor |
| contents | News media coverage of monetary policy is not a passive transcript of central-bank communication: it filters announcements, macroeconomic news, and editorial choices into narratives that move expectations and policy decisions. We embed media sentiment into a behavioral New-Keynesian model in which the central bank reacts to sentiment and sentiment follows an explicit law of motion. We construct monetary-policy sentiment indicators from more than 50,000 Canadian newspaper articles using dictionary methods, transformer models, and a generative-AI framework. Media sentiment shifts household inflation and wage expectations, improves out-of-sample forecasts of GDP growth and inflation, and loads positively on the Bank of Canada's estimated Taylor rule once treated as endogenous. A Bayesian SVAR identifies anticipated and unanticipated monetary-policy shocks together with a narrative shock; the narrative shock contributes a non-trivial share of medium-horizon macroeconomic variance, and a counterfactual that shuts down the dynamic feedback from media sentiment attenuates the propagation of monetary policy to output and prices. %The results suggest that media narratives are an integral part of monetary-policy transmission, not merely an additional source of information. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_15092 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Monetary Policy in the Media Spotlight: Sentiments, Signals, and Economic Impact Ayivodji, Firmin Briand, Etienne Moran, Kevin Stevanovic, Dalibor Econometrics News media coverage of monetary policy is not a passive transcript of central-bank communication: it filters announcements, macroeconomic news, and editorial choices into narratives that move expectations and policy decisions. We embed media sentiment into a behavioral New-Keynesian model in which the central bank reacts to sentiment and sentiment follows an explicit law of motion. We construct monetary-policy sentiment indicators from more than 50,000 Canadian newspaper articles using dictionary methods, transformer models, and a generative-AI framework. Media sentiment shifts household inflation and wage expectations, improves out-of-sample forecasts of GDP growth and inflation, and loads positively on the Bank of Canada's estimated Taylor rule once treated as endogenous. A Bayesian SVAR identifies anticipated and unanticipated monetary-policy shocks together with a narrative shock; the narrative shock contributes a non-trivial share of medium-horizon macroeconomic variance, and a counterfactual that shuts down the dynamic feedback from media sentiment attenuates the propagation of monetary policy to output and prices. %The results suggest that media narratives are an integral part of monetary-policy transmission, not merely an additional source of information. |
| title | Monetary Policy in the Media Spotlight: Sentiments, Signals, and Economic Impact |
| topic | Econometrics |
| url | https://arxiv.org/abs/2605.15092 |