Oil and macroeconomic (in)stability

We analyze the role of oil price volatility in reducing U.S. macroeconomic instability. Using a regime-switching structural model we revisit the timing of the Great Moderation and the sources of changes in the volatility of macroeconomic variables. We find that smaller or fewer oil price shocks did not play a major role in explaining the Great Moderation. Instead oil price shocks are recurrent sources of macroeconomic fluctuations. The most important factor reducing macroeconomic variability is a decline in the volatility of other structural shocks (demand and supply). A change to a more responsive monetary policy regime also played a role

Oil and macroeconomic (in)stability

We analyze the role of oil price volatility in reducing U.S. macroeconomic instability. Using a regime-switching structural model we revisit the timing of the Great Moderation and the sources of changes in the volatility of macroeconomic variables. We find that smaller or fewer oil price shocks did not play a major role in explaining the Great Moderation. Instead oil price shocks are recurrent sources of macroeconomic fluctuations. The most important factor reducing macroeconomic variability is a decline in the volatility of other structural shocks (demand and supply). A change to a more responsive monetary policy regime also played a role

Climate risk and commodity currencies

The positive relationship between real exchange rates and natural resource income is well understood and studied. However, climate change and the transition to a lower-carbon economy now challenges this relationship. We document this by proposing a novel news media-based measure of climate change transition risk and show that when such risk is high, major commodity currencies experience a persistent depreciation and the relationship between commodity price fluctuations and currencies tends to become weaker.publishedVersio

News media vs. FRED-MD for macroeconomic forecasting

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments.publishedVersio

Macroeconomic uncertainty and bank lending

We investigate the impact of macro-related uncertainty on bank lending in Norway. We show that an increase in general macroeconomic uncertainty reduces bank lending. Importantly, however, we show that this effect is largely driven by monetary policy uncertainty, suggesting that uncertainty about the monetary policy stance is key for understanding why macro-related uncertainty impacts bank lending

News media vs. FRED-MD for macroeconomic forecasting

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments

News media vs. FRED-MD for macroeconomic forecasting

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments

News-driven inflation expectations and information rigidities

We investigate the role played by the media in the expectations formation process of households. Using a news-topic-based approach we show that news types the media choose to report on, e.g., (Internet) technology, health, and politics, are good predictors of households' stated inflation expectations. In turn, in a noisy information model setting, augmented with a simple media channel, we document that the underlying time series properties of relevant news topics explain the timevarying information rigidity among households. As such, we not only provide a novel estimate showing the degree to which information rigidities among households vary across time, but also provide, using a large news corpus and machine learning algorithms, robust and new evidence highlighting the role of the media for understanding inflation expectations and information rigidities

Narrative monetary policy surprises and the media

We propose a method to quantify narratives from textual data in a structured manner, and identify what we label "narrative monetary policy surprises" as the change in economic media coverage that can be explained by central bank communication accompanying interest rate meetings. Our proposed method is fast and simple, and relies on a Singular Value Decomposition of the different texts and articles coupled with a unit rotation identification scheme. Identifying narrative surprises in central bank communication using this type of data and identification provides surprise measures that are uncorrelated with conventional monetary policy surprises, and, in contrast to such surprises, have a significant effect on subsequent media coverage. In turn, narrative monetary policy surprises lead to macroeconomic responses similar to what recent monetary policy literature associates with the information component of monetary policy communication. Our study highlights the importance of written central bank communication and the role of the media as information intermediaries

Narrative monetary policy surprises and the media

We propose a method to quantify narratives from textual data in a structured manner, and identify what we label "narrative monetary policy surprises" as the change in economic media coverage explained by central bank communication accompanying interest rate meetings. Our proposed method is fast and simple, and relies on a Singular Value Decomposition of the different texts and articles coupled with a unit rotation identification scheme. Identifying narrative surprises in central bank communication using this type of data and identification provides surprise measures that are uncorrelated with conventional monetary policy surprises, and, in contrast to such surprises, have a significant effect on subsequent media coverage. In turn, narrative monetary policy surprises lead to macroeconomic responses similar to what recent monetary policy literature associates with the information component of monetary policy communication. Our study highlights the importance of written central bank communication and the role of the media as information intermediaries